1. Technical Field
The present invention relates generally to database consolidation, and more particularly to lowering resource cost through Service Level Agreement (SLA)-aware database consolidation using per-tenant memory size configuration.
2. Description of the Related Art
The emergence of cloud computing has induced many new research challenges on database multitenancy. Recent research has investigated the problem of database multitenancy when the workloads of tenants are kept in main memory. For example, OnLine Transaction Processing (OLTP) workloads and in-memory OnLine Analytic Processing (OLAP) workloads have been researched to solve the problem. The assumption that all tenants on a given server must answer their queries from main memory leaves little room for optimization since the buffer size of each tenant is dictated by its working set size, and the Central Processing Unit (CPU) time is dictated by the high throughput requirements of the tenant. Furthermore, none of these solutions is optimized for OLAP workloads whose throughput Service Level Agreements (SLAs) allow for queries to be answered from disk.
Research has also been performed to investigate database multitenancy at a virtual machine level, where the allocation of CPU and memory is the main focus. However, these Virtual Machine (VM)-based methods are not directly applicable to Input/Output (IO)-bound multitenancy at least because IO virtualization technologies cannot currently achieve satisfactory IO isolation with acceptable overhead levels. Another direction of research on database multitenancy focuses on consolidation of large numbers of almost-inactive tenants by sharing the same schema among tenants. The main problem in this type of system is scalability, due to the limit on the number of tables a Database Management System (DBMS) can handle for a given schema.